Volume 14 | Issue 3 |

 Abstract

This paper provides a comprehensive review of Embodied AI. I am writing this because it seems like the next significant trend in AI is the move away off-screen into the real world. Embodied AI implies that the brain of the robot is not a spreadsheet but the information obtained in its body is analyzed and then acted upon in reality. In this paper, 50 of the latest studies are pulled out in which individuals plug in Large Language Models (LLMs) and Multimodal Foundation Models directly into the robot hardware. We divided the review into two sections, the technical grind (how robots plan and manage things they do not know about) and the human one (ethics, social robots, and greener optimizing automation). It happens that the majority of researchers have come to think of LLMs as the so-called high-level brain, which converts human speech into motor commands in the form of Behavior Trees and In-Context Learning. However, we are yet to nail safety, jailbreaking, and the maniacal energy prices.

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 Keywords

Artificial Intelligence, Embodied, Large language model, Robot-LLM

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People's social, political, and economic lives are significantly shaped by leadership. On the other hand, leadership is a very complicated social phenomena. Control and influence are two ideas that are frequently utilized in leadership pattern analysis. In the social structure that operates through control and decision-making, power is a crucial component. In this situation, leadership is ingrained in the social structure. It is a dynamic force that is necessary for any human group endeavor to succeed. No nation or state can prosper without strong leadership. Legislators can be referred to as political leaders since they have a significant influence on how state affairs are managed, including the creation of policies and the adoption of laws that alter the constitutional process. The state needs more and better leaders in every area. Because all organizations and groups in a society need leaders to survive, it is necessary to examine the legislative leadership's complete socioeconomic, cultural, and political history. Kings like Julius Ceasar, Alexander the outstanding, Ashoka the Great, Changez Khan, and Akbar the Great were once outstanding leaders. Napoleon Bonaparte, George Washington, Winston Churchill, Mahatma Gandhi, Jawaharlal Nehru, Indira Gandhi, Draupadi Murmu, Narendra Damodar Das Modi, Mamata Banerjee, and so forth are examples of modern-day leaders. Monarchs were excellent leaders in antiquity, and politicians have taken on leadership roles in the present day.

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 Keywords

leadership, political, politicians, Women, constitution, legislative leadership.

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This paper explores the dualistic struggle for identity in Margaret Atwood's Surfacing (1972) through a bilateral analysis of linguistic alienation and the psychological effects of the island setting. The first section examines the linguistic alienation, adopting Jacques Derrida's concept and critique of logocentrism to argue how the protagonist perceives the English language as a "violent hierarchy" that blemishes her reality. By considering standardised language as a colonial and hegemonic "American" tool of diversification, she undergoes a drastic process of "un-naming" to escape the deceitful nature of the signifier. The second section shifts to the psychological alienation, focusing on the isolated island setting as an intangible space that coerces the transformation of the repressed. Pertaining to the psychological theories of dissociation and loss of identity, this study demonstrates how the island acts as a psychological penitentiary where the protagonist confronts the trauma of her past. Ultimately, the paper discusses how the protagonist's refuge in the woods is not a descent into insanity, but an obligatory psychological "surfacing." By deconstructing both the linguistic structures of society and the psychological restraints on her, she attains a unified consciousness, moving from a dissociated "floating head" to something coherent and rational.

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 Keywords

Linguistic Alienation, Logocentrism, Psychological Setting, Dissociation, Trauma Recovery, Margaret Atwood.

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The rapid advancement of Internet of Things (IoT) technology has enabled the development of smart healthcare systems for real-time patient monitoring. This paper presents the design and implementation of an Intelligent Healthcare Monitoring System using IoT and TensorFlow for continuous tracking and predictive analysis of vital health parameters. The proposed system integrates biomedical sensors to measure heart rate, body temperature, and oxygen saturation (SpO?), which are interfaced with a microcontroller for data acquisition and preprocessing. The collected data is transmitted to a cloud platform via a Wi-Fi module, enabling remote monitoring through web or mobile applications. A machine learning model developed using TensorFlow analyses the real-time sensor data to detect abnormal patterns and predict potential health risks. In case of critical conditions, the system generates instant alerts to caregivers and medical professionals to ensure timely intervention. The proposed solution is cost-effective, portable, and suitable for home?based as well as hospital monitoring. Experimental results demonstrate reliable data transmission, accurate prediction performance, and effective real-time alert generation. The system enhances patient safety, reduces frequent hospital visits, and contributes to the advancement of smart and connected healthcare solution

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 Keywords

Internet of Things (IoT), Healthcare Monitoring, Machine Learning, TensorFlow, Remote Patient Monitoring, Biomedical Sensors, Cloud Computing, Real-Time Data Analysis, Smart Healthcare, Early Disease Detection

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This study examines the impact of second screen engagement on consumer attention toward television advertisements during live cricket broadcasts among young adults in urban India. With the rapid proliferation of smartphones and affordable internet access, simultaneous media consumption has become a dominant viewing behavior, particularly in a cricket-centric market like India. Adopting a quantitative, descriptive-correlational research design, primary data were collected from 528 respondents aged 18-35 through a structured online questionnaire. The findings reveal that second screen usage is highly prevalent, with social media browsing and messaging emerging as the most common concurrent activities. Importantly, 69% of respondents reported that second screen engagement distracts them from television advertisements, indicating a significant negative effect on advertising attention. The study rejects the null hypothesis and confirms that divided attention reduces the effectiveness of traditional TV advertising during cricket matches. The research highlights the need for advertisers to shift toward integrated, multi-platform strategies that align television and digital media to effectively engage audiences in a fragmented media environment. These findings contribute to the growing literature on multi-screen behavior and offer practical insights for marketers operating in sports broadcasting contexts.

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 Keywords

Second screen engagement, cricket advertising, consumer attention, multi-screen behavior, advertising effectiveness, digital media, urban India, sports marketing, media multitasking, integrated marketing communication

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MindAI Therapy is an AI-based mental wellness assistant designed to provide real-time emotional support through intelligent conversation. The system uses a locally deployed Large Language Model (LLaMA 3 via Ollama) along with Natural Language Processing techniques to understand user input and generate empathetic responses. It integrates a Flask backend, a web-based chat interface, and voice interaction using Web Speech API and pyttsx3 for a natural user experience.

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 Keywords

MindAI, Mental Health AI, Psychotherapy Chatbot, Large Language Models (LLM), LLaMA 3, Ollama, Natural Language Processing (NLP), Conversational AI, Emotion Detection, Voice Interaction, Human-Computer Interaction (HCI), Flask, LangChain, Privacy-Preserving AI

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The transition from hospital to home following surgical procedures represents a critical phase in patient recovery, often associated with increased risks of complications, readmissions, and gaps in continuity of care. Traditional post-discharge models relying on periodic in-person follow-ups are frequently inadequate in addressing patients' dynamic recovery needs. In recent years, telehealth and digital health innovations have emerged as transformative tools to bridge this gap and enhance postoperative care. This review explores the role of telehealth interventions, including virtual consultations, remote patient monitoring, mobile health applications, and artificial intelligence-driven analytics, in improving post-discharge surgical outcomes. Evidence suggests that telehealth facilitates early detection of complications, improves patient engagement, enhances adherence to treatment plans, and significantly reduces unnecessary hospital visits and healthcare costs. Remote monitoring devices enable continuous assessment of vital parameters, while mobile applications support education, symptom tracking, and real-time communication with healthcare providers. Furthermore, artificial intelligence enhances risk prediction and personalized care planning, contributing to proactive and preventive healthcare delivery. Despite these advantages, challenges such as digital literacy, data privacy concerns, technological infrastructure limitations, and regulatory barriers persist, particularly in low-resource settings. Addressing these challenges is essential to ensure equitable access and effective implementation. Overall, telehealth and digital innovations hold substantial potential to revolutionize post-discharge surgical care by promoting patient-centered, accessible, and cost-effective healthcare delivery. Future research should focus on long-term outcomes, scalability, and integration of emerging technologies into standard surgical care pathways.

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Keywords: Telehealth, Post-discharge care, Surgical care, Digital health, Remote monitoring, Mobile health, Artificial intelligence, Patient outcomes, Healthcare innovation, Continuity of care

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 Abstract

Youth act as the real oars that propel the wellbeing of society. They have the capacity to lead the society through their knowledge, enthusiasm, potential, expertise, innovation, determination and commitment. If we cultivate their character through essential values, it serves as a catalyst that yields longitudinal societal benefits. The developmental stage of an individual is crucial for empowerment. Therefore, holistic guidance and support make them active participants in the global world. The National Education policy 2020 is here to revitalize the whole education system of India which equips students to navigate in this swiftly changing world of the 21st century. The main focus of this policy is to build a holistic learner, giving it the status of knowledgeable and vibrant country. This paper aims to provide a comprehensive analysis of the proposed policy guidelines towards youth empowerment through its significant attributes by revitalizing the Educational landscape. Education enlightens the youth as productive citizens by unlocking their fullest possible potential to build a progressive nation. Individuals with skills and wisdom can become a resource for the sustainable growth of the society. So this analysis is an exploration of how NEP 2020 may as well be a hub for experiential, flexible, multidisciplinary, and transformative educational practices which will empower the youth of the 21st century. NEP 2020 facilitates employability by transforming an individual into a human resource with globally relevant skills and training through their revolutionary guidelines in education to promote economic growth. NEP 2020 reforms Education as a powerful catalyst for youth empowerment by instilling life skills, ethics, responsibility, resilience, democratic spirit, and decision-making capabilities in youth to make them globally competent. This discussion attempts to establish a linkage between the transformative policy guidelines and their practical implications for making holistic global citizens to build a sustainable society.

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 Keywords

National Education Policy 2020, Educational Landscape, Youth Empowerment

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 Abstract

Objectives Hypothesis

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Effectiveness, Structured Teaching Programme, Knowledge, Prevention of Breast Cancer, Women.

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This paper presents a Software Defined Networking (SDN)-based DDoS (Distributed Denial of Service) attack detection and mitigation system using the Ryu SDN controller with an integrated 1D Convolutional Neural Network (1D-CNN). The proposed system implements a three-layer hierarchical detection architecture comprising a Hard Threshold layer for high-intensity attacks (PPS > 5000), a Soft Threshold layer powered by a 1D-CNN classifier for medium-intensity attacks (1000 < PPS < 5000), and a Multi-Feature Rule-Based layer for low-intensity attacks (PPS < 1000). The system is deployed on a Mininet-simulated network topology consisting of 18 hosts across 6 OpenFlow switches. A three-strike violation tracking mechanism escalates repeated offenders from temporary port blocking to permanent mitigation. A real-time web dashboard at localhost:8080 provides live detection alerts, blocked port management, and admin controls with email notification capabilities. Experimental results demonstrate effective detection across all attack intensities with automated mitigation response times under 30 milliseconds.

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 Keywords

DDoS Detection, Software Defined Networking, 1D-CNN, Ryu Controller, OpenFlow, Mininet, Intrusion Detection System, Network Security, Deep Learning, Port Blocking.

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Creative Commons Attribution 4.0 and The Open Definition